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Soft Tissue Deformation Model Based on marquardt algorithm and Enrichment Function

Computer Modeling in Engineering & Sciences 2020年第9期124卷 1131-1147页

作者： Xiaorui Zhang Xuefeng Yu Wei Sun Aiguo Song Jiangsu Engineering Center of Network Monitoring Engineering Research Center of Digital ForensicsMinistry of EducationSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and ControlSchool of Instrument Science and EngineeringSoutheast UniversityNanjing210096China

In order to solve the problem of high computing cost and low simulation accuracy caused by discontinuity of incision in traditional meshless model,this paper proposes a soft tissue deformation model based on the marquardt algorithm and enrichment *** model is based on the element-free Galerkin method,in which Kelvin viscoelastic model and adjustment function are *** algorithm is applied to fit the relation between force and displacement caused by surface deformation,and the enrichment function is applied to deal with the discontinuity in the meshless *** verify the validity of the model,the Sensable Phantom Omni force tactile interactive device is used to simulate the deformations of stomach and *** results show that the proposed model improves the real-time performance and accuracy of soft tissue deformation simulation,which provides a new perspective for the application of the meshless method in virtual surgery.

关键词： Virtual surgery meshless model marquardt algorithm enrichment function soft tissue simulation

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Improved marquardt algorithm for Training Neural Networks for Chemical Process Modeling

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Tsinghua Science and Technology 2002年第5期7卷 454-457页

作者：吴建昱何小荣 Department of Chemical Engineering Tsinghua University Beijing 100084 China

Back-propagation (BP) artificial neural networks have been widely used to model chemical processes. BP networks are often trained using the generalized delta-rule (GDR) algorithm but application of such networks is limited because of the low convergent speed of the algorithm. This paper presents a new algorithm incorporating the marquardt algorithm into the BP algorithm for training feedforward BP neural networks. The new algorithm was tested with several case studies and used to model the Reid vapor pressure (RVP) of stabilizer gasoline. The new algorithm has faster convergence and is much more efficient than the GDR algorithm.

关键词： neural network marquardt algorithm training

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Comparative study of kinetic modeling for the oxidative coupling of methane by genetic and marquardt algorithms

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Journal of Natural Gas Chemistry 2010年第3期19卷 293-299页

作者： Shahrnaz Mokhtari Ali Vatani Nastaran Razmi Farooji Iran Polymer and Petrochemical Institute Faculty of Engineering university of Tehran

Overall kinetic studies on the oxidative coupling of methane,OCM,have been conducted in a tubular fixed bed reactor,using perovskite titanate as the reaction *** appropriate operating conditions were found to be：temperature 750-775 ℃,total feed flow rate of 160 ml/min,CH4 /O2 ratio of 2 and GHSV of 100·min-1 .Under these conditions,C 2 yield of 28% was *** of the kinetic data have been performed with lumped rate equations for C2 and COx formation as functions of temperature,O2 and CH4 partial *** models have been selected among the common lumped kinetic *** selected models have been regressed with the experimental data which were obtained from the Catatest system by genetic algorithm in order to obtain optimized *** kinetic coefficients in the overall reactions were optimized by different numerical optimization methods such as：the Levenberg-marquardt and genetic algorithms and the results were compared with one *** has been found that the Santamaria model is in good agreement with the experimental *** Arrhenius parameters of this model have been obtained by linear *** should be noted that the marquardt algorithm is sensitive to the first guesses and there is possibility to trap in the relative minimum.

关键词： oxidative coupling of methane kinetics perovskite genetic algorithm marquardt algorithm

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